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This paper addresses the practical challenges in sitting volleyball training, including long-term reliance on coaches’ experience, insufficient data support, and elevated injury risks. It explores pathways for applying intelligent technologies to enhance scientific training in this discipline. Through a one-month randomised controlled trial involving 30 athletes from the Chinese National Sitting Volleyball Team, the study examined whether the integration of artificial intelligence, multimodal sensors, and virtual reality technologies could improve technical proficiency and reduce injury risks among sitting volleyball players. Findings reveal that the intelligent training system significantly elevated athletes’ technical and tactical proficiency. The experimental group demonstrated a surge in the success rate of position 4 spikes from 62.3% to 85.8%, a 19.4% increase in serve-block efficiency, a 50% reduction in tactical response time, and a 33% improvement in optimised hitting trajectory rates. Regarding injury prevention, real-time monitoring and alerts reduced lumbar fasciitis incidence from 45.5% to 26.8%, lowered lumbar spine load by 34% for athletes with spinal cord injuries, and markedly decreased shoulder strain rates. Sensors and equipment tailored to different disability types achieved 100% acceptance and high satisfaction among athletes, with a system usability score of 86.4 reflecting excellent user experience. The findings indicate that intelligent technology proves highly beneficial in sitting volleyball training. It holds significant value for enhancing competitive performance and reducing injury risks. This facilitates a shift in coaching methodologies from reliance on traditional experience towards data-driven approaches. It provides a technical model and practical reference for the scientific and personalised development of disabled sports. Future research could be deepened by expanding sample sizes, extending study durations, and reducing technological costs to promote the wider adoption of intelligent training systems across disabled sports.

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Smarter Training for Safer Play: A VR-Enhanced System Tested in Elite Sitting Volleyball

  • 会议论文

  • 发表日期：

    2026年

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  • Cai Yong,
  • Dai Jie

摘要

This paper addresses the practical challenges in sitting volleyball training, including long-term reliance on coaches’ experience, insufficient data support, and elevated injury risks. It explores pathways for applying intelligent technologies to enhance scientific training in this discipline. Through a one-month randomised controlled trial involving 30 athletes from the Chinese National Sitting Volleyball Team, the study examined whether the integration of artificial intelligence, multimodal sensors, and virtual reality technologies could improve technical proficiency and reduce injury risks among sitting volleyball players. Findings reveal that the intelligent training system significantly elevated athletes’ technical and tactical proficiency. The experimental group demonstrated a surge in the success rate of position 4 spikes from 62.3% to 85.8%, a 19.4% increase in serve-block efficiency, a 50% reduction in tactical response time, and a 33% improvement in optimised hitting trajectory rates. Regarding injury prevention, real-time monitoring and alerts reduced lumbar fasciitis incidence from 45.5% to 26.8%, lowered lumbar spine load by 34% for athletes with spinal cord injuries, and markedly decreased shoulder strain rates. Sensors and equipment tailored to different disability types achieved 100% acceptance and high satisfaction among athletes, with a system usability score of 86.4 reflecting excellent user experience. The findings indicate that intelligent technology proves highly beneficial in sitting volleyball training. It holds significant value for enhancing competitive performance and reducing injury risks. This facilitates a shift in coaching methodologies from reliance on traditional experience towards data-driven approaches. It provides a technical model and practical reference for the scientific and personalised development of disabled sports. Future research could be deepened by expanding sample sizes, extending study durations, and reducing technological costs to promote the wider adoption of intelligent training systems across disabled sports.